Analysis of Noise Removal Techniques on Retinal Optical Coherence Tomography Images

In the biomedical field, automatic disease detection by image processing has become the norm in the current days. For early illness detection, ophthalmologists have explored a variety of invasive and noninvasive procedures. Optical Coherence Tomography (OCT) is a noninvasive imaging technique for obtaining high resolution tomographic images of biological systems. The image quality is degraded by noise, which degrades the performance of noisy image processing algorithms. The OCT images captured with speckle noise and prior to further processing, it is critical to use an effective approach for denoising the image. In this paper, we used Median filter, Average filter or Mean filter, Wiener filter, Gaussian filter and Bilateral filter on OCT images in this paper, and discussed the advantages and drawbacks of each approach. The effectiveness of these filters are compared using the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Contrast to Noise Ratio (CNR).

@article{Sheeba2022,
  title     = {Analysis of Noise Removal Techniques on Retinal Optical Coherence Tomography Images},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {9},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {T. M. Sheeba and S. Albert Antony Raj},
  doi       = {10.14569/IJACSA.2022.0130948},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130948}
}